Innovating Social Management and Digital Governance Through Big Data Visualization and Analytical Techniques

Meng Chai; Doris Wong Hooi Ten

doi:10.54254/2754-1169/2025.LH25754

Advances in Economics, Management and Political SciencesOpen access

Innovating Social Management and Digital Governance Through Big Data Visualization and Analytical Techniques

Research Article

Open Access

Innovating Social Management and Digital Governance Through Big Data Visualization and Analytical Techniques

Meng Chai ¹, Doris Wong Hooi Ten ^2*

¹ Universiti Teknologi Malaysia

² Universiti Teknologi Malaysia

^*Corresponding author: chaimeng@graduate.utm.my

Published on 6 August 2025

AEMPS Vol.207

ISSN (Print): 2754-1177

ISSN (Online): 2754-1169

ISBN (Print): 978-1-80590-299-7

ISBN (Online): 978-1-80590-300-0

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Abstract

This paper aims to explore the innovation of social management system and digital governance based on big data visualization analysis. Firstly, the relevant technologies and theories are introduced, including an overview of Hadoop and Spark, as well as the significance of data visualization. Then, a social management event data classification and governance algorithm based on improved Naive Bayes classification algorithm is proposed, and a big data-driven social management system innovation system is designed. This system includes modules for data warehouse, data collection, and statistical analysis. Through experiments and evaluations, the improved Naive Bayes algorithm is proven to have accurate classification and effective performance on social management event data in a standalone environment. This research provides support and assistance for social management decision-making and proposes future research directions, including algorithm optimization and system scalability.

Keywords:

Big data visualization analysis, Social management system, Digital governance, Hadoop, Spark, Improved Naive Bayes classification algorithm

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References

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References

[1]. Hang Z. Research and Design of Real Time Big Data Visualization Analysis Platform Based on Flink [J]. Journal of Physics: Conference Series, 2023(1): 2504.

[2]. Xiaoming L, Wei Y, Guangquan X, et al. MSDA-NMF: A Multilayer Complex System Model Integrating Deep Autoencoder and NMF [J]. Mathematics, 2022: 10-15.

[3]. Li M, Du W, Qian F, et al. Total plant performance evaluation based on big data: Visualization analysis of TE process [J]. Chinese Journal of Chemical Engineering, 2018(8): 26.

[5]. Mathias D, Steven L. Topological genealogy: a methodology to research transnational digital governance in/through/as change [J]. Journal of Education Policy, 2023(1): 38.

[9]. WANG H, FANG W, SHI C. On the Construction of Chinese Government Procurement of Public Service Assessment System [J]. Cross-Cultural Communication, 2015(8): 11.

Cite this article

Chai,M.;Ten,D.W.H. (2025). Innovating Social Management and Digital Governance Through Big Data Visualization and Analytical Techniques. Advances in Economics, Management and Political Sciences,207,32-42.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICEMGD 2025 Symposium: Innovating in Management and Economic Development

ISBN: 978-1-80590-299-7(Print) / 978-1-80590-300-0(Online)

Editor: Florian Marcel Nuţă Nuţă, Ahsan Ali Ashraf

Conference website: https://2025.icemgd.org/Lahore.html

Conference date: 23 September 2025

Series: Advances in Economics, Management and Political Sciences

Volume number: Vol.207

ISSN: 2754-1169(Print) / 2754-1177(Online)

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